Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 306 334 945 657 633 636 325 450 251 283 241 47 596 727 878 743 452 348 239 498
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 241 325 47 450 306 NA 251 334 NA 452 283 636 348 878 657 945 596 NA 498 239 633 727 743
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 1 5 4 3 3 3 4 1 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "w" "t" "g" "l" "i" "L" "K" "O" "J" "I"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 3
which( manyNumbersWithNA > 900 )
[1] 16
which( is.na( manyNumbersWithNA ) )
[1] 6 9 18
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 945
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 945
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 945
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "L" "K" "O" "J" "I"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "w" "t" "g" "l" "i"
manyNumbers %in% 300:600
[1] TRUE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 1 2 7 8 13 17 18 20
sum( manyNumbers %in% 300:600 )
[1] 8
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "small" "small" "small" NA "small" "small" NA "small" "small" "large" "small" "large" "large" "large" "large" NA "small" "small" "large"
[22] "large" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "small" "small" "small" "UNKNOWN" "small" "small" "UNKNOWN" "small" "small" "large" "small" "large" "large" "large" "large"
[18] "UNKNOWN" "small" "small" "large" "large" "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 0 0 0 NA 0 0 NA 0 0 636 0 878 657 945 596 NA 0 0 633 727 743
unique( duplicatedNumbers )
[1] 2 1 5 4 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 1 5 4 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 16
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 945
which.min( manyNumbersWithNA )
[1] 3
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 47
range( manyNumbersWithNA, na.rm = TRUE )
[1] 47 945
manyNumbersWithNA
[1] 241 325 47 450 306 NA 251 334 NA 452 283 636 348 878 657 945 596 NA 498 239 633 727 743
sort( manyNumbersWithNA )
[1] 47 239 241 251 283 306 325 334 348 450 452 498 596 633 636 657 727 743 878 945
sort( manyNumbersWithNA, na.last = TRUE )
[1] 47 239 241 251 283 306 325 334 348 450 452 498 596 633 636 657 727 743 878 945 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 945 878 743 727 657 636 633 596 498 452 450 348 334 325 306 283 251 241 239 47 NA NA NA
manyNumbersWithNA[1:5]
[1] 241 325 47 450 306
order( manyNumbersWithNA[1:5] )
[1] 3 1 5 2 4
rank( manyNumbersWithNA[1:5] )
[1] 2 4 1 5 3
sort( mixedLetters )
[1] "g" "i" "I" "J" "K" "l" "L" "O" "t" "w"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 6.5 1.5 4.0 6.5 10.0 4.0 8.5 1.5 8.5 4.0
rank( manyDuplicates, ties.method = "min" )
[1] 6 1 3 6 10 3 8 1 8 3
rank( manyDuplicates, ties.method = "random" )
[1] 6 2 5 7 10 3 9 1 8 4
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 0.2212481 -0.4826574 -2.4718006 -0.9079842 -1.3694906 0.6877984 1.0930027 -0.1856917 -0.1215355 0.4844100
round( v, 0 )
[1] -1 0 0 0 1 0 0 -2 -1 -1 1 1 0 0 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.2 -0.5 -2.5 -0.9 -1.4 0.7 1.1 -0.2 -0.1 0.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.22 -0.48 -2.47 -0.91 -1.37 0.69 1.09 -0.19 -0.12 0.48
floor( v )
[1] -1 -1 0 0 1 0 -1 -3 -1 -2 0 1 -1 -1 0
ceiling( v )
[1] -1 0 0 1 1 1 0 -2 0 -1 1 2 0 0 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
Copyright © 2023 Biomedical Data Sciences (BDS) | LUMC